Compliance validation and diagnosis of business data constraints in business processes at runtime

Abstract

Business processes involve data that can be modified and updated by various activities at any time. The data involved in a business process can be associated with flow elements or data stored. These data must satisfy the business compliance rules associated with the process, where business compliance rules are policies or statements that govern the behaviour of a company. To improve and automate the validation and diagnosis of compliance rules based on the description of data semantics (called Business Data Constraints), we propose a framework where dataflow variables and stored data are analyzed. The validation and diagnosis process is automated using Constraint Program-ming, to permit the detection and identification of possibly unsatisfiable Business Data Constraints, even if the data involved in these constraints are not all instantiated. This implies that the potential errors can be determined in advance. Furthermore, a language to describe Business Data Constraints is proposed, for the improvement of user-oriented aspects of the business process description. This language allows a business expert to write Business Data Constraints that will be automatically validated in run-time, without the support of an information technology expert.